Robotics - LAAS-CNRS

Department rob

Robotics

The robotics department is developing a multi-thematic field of research focusing on the development of perception, decision, movement generation and communication functions for robots, intended to be tested in real, uncontrolled environments. It is equipped with a very complete robotic platform.

head

Philippe Soueres

The department is structured into three research teams which work in synergy and whose areas of expertise are complementary.

The “Gepetto” team, specialist in the movement of anthropomorphic systems, has three research objects: the humanoid robot, the digital mannequin and Human. Its expertise is focused on the planning, generation and control of the movement of these unstable poly-articulated systems. It carries out interdisciplinary activity at the intersection of robotics, neuroscience and biomechanics with a particular interest in the design of artificial muscles.

The activity of the “Robotics, action and perception” (RAP) team, experts in signal processing, is centered on the “perception-action” link, with a focus on vision and hearing. Its areas of research are: detection, segmentation, identification and tracking of people and objects; perception and control in a dynamic environment and the development of integrated sensors. The challenges to be met are taking into account the variability of the environment and the constraints of embedding and real-time calculation. The team develops original solutions emphasizing probabilistic data fusion.

The “Robotics and its interactions” (RIS) team focuses its expertise on interactions with humans and the environment. Its activities cover systems architecture, physical control and interactions, temporal planning and reasoning, motion planning and learning. The methods and algorithms developed are exploited in three main areas: terrestrial and aerial robotics, with a strong focus on multi-robot cooperation and environment modeling, cognitive and interaction robotics and molecular movement.

These three teams maintain close collaboration with each other, as well as with other laboratory teams attached to different scientific departments. Their work is carried out within the framework of a large number of European projects (ESA, FP7, Horizon Europe, EraNet, etc.), national and regional, and direct industrial collaborations. The applications concern a wide range of fields: agriculture, transport, factory of the future, service robotics, home automation and ambient intelligence, virtual reality and animation, surveillance and civil security, planetary and space exploration, biochemistry, etc.

A large number of software developed by the department researchers are distributed in open access (GenoM3, GDHE, OpenPRS, Jafar, HPP, SoT, Pinocchio, etc.).

AREAS OF

RESEARCH AND APPLICATIONS

DISCIPLINARY FIELDS

COVERED IN OUR DEPARTMENT

DEPARTMENT TEAMS

The department is composed of 3 research teams: Robotique et Interactions (RIS), Robotique, Action, Perception (RAP) et GEPETTO.

gepetto

Olivier Stasse

The research activity of the Gepetto team is focused on the analysis and generation of movement of anthropomorphic systems. Created in 2006, it quickly became one of the leading teams in humanoid robotics, unanimously recognized for its expertise in movement …

rap

Patrick Danes

Texte à modifier dans l’interface d’édition: champ 'description' de la page Equipe.

ris

Simon Lacroix

The "Robotics and InteractionS" team develops a research project on autonomous mobile machines that integrate perception, reasoning, learning, action and reaction capabilities. The challenge is on their capacity to act rationally in dynamic environments to achieve a large variety of …

Latest publications

2024

Journal articles

Eliott Lumet, Thomas Jaravel, Mélanie C Rochoux, Olivier Vermorel, Simon Lacroix. Assessing the Internal Variability of Large-Eddy Simulations for Microscale Pollutant Dispersion Prediction in an Idealized Urban Environment. Boundary-Layer Meteorology, 2024, 190 (2), pp.9. ⟨10.1007/s10546-023-00853-7⟩. ⟨hal-04425945v2⟩

Nathalie Tarrat, J. Christian Schön, Juan Cortés. Dependence of lactose adsorption on the exposed crystal facets of metals: a comparative study of gold, silver and copper. Physical Chemistry Chemical Physics, 2024, 31, pp.21134-21146. ⟨10.1039/D4CP01559B⟩. ⟨hal-04664324⟩

Simon Wasiela, Marco Cognetti, Paolo Robuffo Giordano, Juan Cortés, Thierry Simeon. Robust Motion Planning with Accuracy Optimization based on Learned Sensitivity Metrics. IEEE Robotics and Automation Letters, 2024, 9 (11), pp.10113-10120. ⟨hal-04636547⟩

Gaël Loubet, Alassane Sidibe, Philippe Herail, Alexandru Takacs, Daniela Dragomirescu. Autonomous Industrial IoT for Civil Engineering Structural Health Monitoring. IEEE Internet of Things Journal, 2024, 11 (5), pp.8921 - 8944. ⟨10.1109/JIOT.2023.3321958⟩. ⟨hal-04247382⟩

Olga Napolitano, Marco Cognetti, Lucia Pallottino, Dimitrios Kanoulas, Paolo Salaris, et al.. Active Sensing for Data Quality Improvement in Model Learning. IEEE Control Systems Letters, 2024, pp.1-1. ⟨10.1109/LCSYS.2024.3410152⟩. ⟨hal-04226725v2⟩

Gianni Lunardi, Thomas Corbères, Carlos Mastalli, Nicolas Mansard, Thomas Flayols, et al.. Reference-Free Model Predictive Control for Quadrupedal Locomotion. IEEE Access, 2024, 12, pp.689 - 698. ⟨10.1109/access.2023.3345157⟩. ⟨hal-04730351⟩

Valentin Milia, Nathalie Tarrat, Christophe Zanon, Juan Cortés, Mathias Rapacioli. Exploring Molecular Energy Landscapes by Coupling the DFTB Potential with a Tree-Based Stochastic Algorithm: Investigation of the Conformational Diversity of Phthalates. Journal of Chemical Information and Modeling, 2024, 64 (8), pp.3290-3301. ⟨10.1021/acs.jcim.3c01981⟩. ⟨hal-04517230⟩

Quentin Le Lidec, Wilson Jallet, Louis Montaut, Ivan Laptev, Cordelia Schmid, et al.. Contact Models in Robotics: a Comparative Analysis. IEEE Transactions on Robotics, 2024, 40, pp.3716 - 3733. ⟨10.1109/TRO.2024.3434208⟩. ⟨hal-04067291v3⟩

Antoine Rouxel, Antoine Monmayrant, Simon Lacroix, Henri Camon, Sébastien Lopez. Accurate ray-tracing optical model for coded aperture spectral snapshot imagers. Applied optics, 2024, 63 (7), pp.1828. ⟨10.1364/AO.515775⟩. ⟨hal-04474346⟩